Build Data Integration Pipelines
The C3 Agentic AI Platform allows data engineers to build production-ready pipelines with significantly less code through a metadata-driven approach.
To build a Data Pipeline on the C3 Agentic AI Platform
- Establish a connection to the source system.
- Map the necessary schemas.
- Specify any required data transformations.
- Configure Execution Criteria for the pipeline.
By following these steps, data engineers can leverage the C3 Agentic AI Platform to create production-ready pipelines with significantly less code.
After declaring the pipeline, no extra code is required for:
Ensuring the performance, scalability, and reliability of the pipeline
Viewing real-time or historical monitoring of the pipeline and the data that it transforms
Contextual error logging and recovery of pipeline failures
Tracking data lineage and provenance
This declarative approach significantly accelerates the time-to-value, and reduces the total cost of ownership for building and operating production data pipelines.
In the platform, canonical data models are built using SourceSystem, SourceCollection, Source, Canonical, and Transform Types. To learn more about these Types, see Data Pipeline Architecture.